测试结果验证了算法在求解动态车辆调度问题中的有效性。
The test results demonstrate the effectiveness of the RHSA to solve the dynamic vehicle scheduling problem.
最后,在以上研究的基础之上,开发了一套基于蚁群算法的动态车辆调度系统,并将此系统与其他动态车辆调度系统做了比较和分析。
Finally, this thesis develops a dynamic vehicle scheduling system based on ant colony algorithm and compares this system with other dynamic vehicle scheduling systems.
仿真试验表明,该算法不仅提高了最优解的质量,而且还具有搜索空间小、求解速度快的特点,能够有效地解决大规模动态车辆调度问题。
The simulation results show that the proposed algorithm can not only improve the optimal solution, but also reduce greatly the search space and computation time, and can solve the problem efficiently.
应用推荐